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--- |
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license: apache-2.0 |
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base_model: openai/whisper-large-v3 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: Whisper Large Korean/English |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Whisper Large Korean/English |
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This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- eval_loss: 0.1397 |
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- eval_wer: 8.2666 |
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- eval_runtime: 6120.463 |
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- eval_samples_per_second: 0.827 |
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- eval_steps_per_second: 0.103 |
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- epoch: 6.0 |
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- step: 7590 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 1265 |
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- training_steps: 12650 |
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- mixed_precision_training: Native AMP |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.0.1 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
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